High Traffic Rates Research Articles

How do Road Users in Mixed Traffic Perceive Risk Towards Each Other? A Comparative Study from a Developing Country

Many developing countries have high traffic accident rates due to the mixed traffic environment in which bicycles and motor vehicles travel in the same lanes. This paper examines the perceived risk among road users in mixed traffic. A questionnaire survey was used to obtain demographic information and self-reported risk perception among cyclists, motorcyclists, and drivers. Statistical analyses, including the T-test and ANOVA, were used to examine the relevant differences in risk assessment among the groups. The results demonstrate that the groups differ significantly in sociodemographic characteristics, driving experience, and travel characteristics. For self-reported perceived risk, the respondents’ perceptions of road surface conditions, the potential of daydreaming while operating a vehicle, and distraction from passengers or riding companions exhibited significant differences between the groups. The research findings could be beneficial as a guide for policymakers in planning road safety awareness to reduce risk in mixed traffic environments.

Social sustainability in urban mobility: An approach for policies and urban planning from the Global South

Historically, transportation projects and urban mobility policies overlook the dimension of social sustainability, mainly focusing on economic and environmental criteria. This neglect, seen enhanced in the Global South, leads to long travel times, growing congestion, reliance on motorcycles, high traffic accident rates, and limited access to public transport, jobs, and urban facilities, especially for the more vulnerable population. In light of these issues, this paper proposes the Social Sustainability of Urban Mobility (SSUM) approach as an analytical framework that assesses the state of social sustainability in urban mobility by applying a Systematic Literature Review where three gaps were found. First, by tailoring the SSUM approach to the context of the Global South, it is possible to address the population-focused gap in urban mobility. Second, in the literature review, a theoretical gap defining social sustainability in urban mobility and its three primary categories has yet to reach a consensus among practitioners and academics. Finally, more empirical research should be conducted to discuss methodological aspects of operationalizing the SSUM approach through the three main categories: accessibility, the sustainability of the community, and institutionality. The SSUM approach promotes implementing a sustainable urban agenda that builds inclusive, equitable, and just cities in urban mobility.

Why frequent traffic accidents at highway tunnel exit? – An experimental analysis of the slack effect

This study analyzes the causes of frequent traffic accidents at the exit areas of highway tunnels. Vehicle experiments were conducted to collect data on the light environment, vehicle speed, and driver eye movement. The distribution patterns of the illumination, vehicle speed, and gaze location occupancy were analyzed, and highway tunnels of different lengths were compared. The tunnel exit area is divided into the transition, exit, and departure zones. It was observed that there was an obvious white-hole effect at the exit zone, with drastic changes in the light environment. The presence of abnormal acceleration behavior in the transition zone and decreased attention in the departure zone demonstrate the existence of psychological and physiological slack in drivers. Additionally, the tunnel length positively correlates to the slack effect, which is stronger in extra-long tunnels than in the short and medium tunnels. Multiple control scenarios were established and driving simulation experiments were conducted to further analyze the impact of the slack effect on the traffic safety. The experimental results demonstrated that the slack effect of the extra-long tunnels exhibited an evident lag which was still present after leaving the tunnel exit. The average vehicle speed and trajectory offset were larger and more discrete in the post-tunnel zone than on an ordinary open road. The speed of the curve in the post-tunnel zone is 5.1 % higher than that of the curve in the ordinary road, and the maximum trajectory offset is 54.3 % higher. Thus, this study reveals the slack effect at tunnel exits and explains the abnormal phenomenon of relatively good traffic environments but high traffic accident rates in the transition and departure zones of tunnel exits. These results present considerable practical significance for the safe operation of highway tunnels, particularly extra-long tunnels.

Methodology for microclimatic urban canyon design case study surrounding MUST university campus in Cairo

ABSTRACT Climate change is a major issue all over the world which has a great impact on global warming especially in countries with hot arid climates like Egypt. With rapid urbanization, streets in Greater Cairo and new cities are mostly car-oriented, which increases the Urban Heat Island(UHI) and, hence, affects the overall outdoor thermal comfort. Looking at the urban development in recent years, almost 10 new private universities are in operation in Cairo’s new cities together with a number of large recreational projects where they lack the appropriate vegetation surrounding their borders which in turn increases the UHI effect, decreasing the walkability’s thermal comfort and in turn contributes poorly to the surrounding climate. This paper focuses on the urban canyons in streets surrounding universities as they usually have high traffic rates in terms of both vehicular and pedestrian flows. This large flow of pedestrians necessitates taking into consideration the thermal comfort of the users. MUST University in the Al-Motamayez district on the 6th of October city was chosen as a case study. This case study is considered the basis for achieving an understanding and developing a methodology approach for such studies by using Envi-Met software for the simulation of different scenarios focusing on choosing trees appropriate to the climate zone of the city. Results for the simulation of suggested scenarios of intervention show a 30% improvement toward thermal comfort, which could be considered a first step for future guidelines development toward achieving thermal comfort and decreasing UHI.

Traffic rate agnostic end-to-end delay optimization using receiver-based adaptive link scheduling in 6TiSCH networks

Link scheduling is a key component in 6TiSCH networks. It mainly specifies a node is allowed to transmit packets through which link at what time and in which channel. There exist many link scheduling schemes in the literature for 6TiSCH networks. Among the distributed schemes, the Self-healing distributed scheduling for end-to-end delay optimization (Stratum) was specifically devised to minimize end-to-end latency. However, it performs worse in case of higher traffic rates. On the other hand, the de-facto link scheduling standard Minimal Scheduling Function (MSF) allocates cells (i.e. timeslot and channel) randomly in a slotframe for scheduling transmissions, and thus its end-to-end delay performance is not good under all traffic rates. Therefore, this paper proposes a traffic rate agnostic distributed link scheduling function (RTDS) for 6TiSCH networks. The RTDS follows a receiver-based cell selection and allocation strategy to reduce the waiting time of a packet in the buffer of receiving node before forwarding the packet towards final destination. Unlike MSF, the RTDS uses lesser number of control packet exchanges to adapt the schedule of a link based on the present network condition and traffic rate. The proposed RTDS scheme minimizes end-to-end latency under any traffic rate. RTDS is implemented in the 6TiSCH simulator. Simulation results show that RTDS can significantly improve the end-to-end latency compared to the benchmark schemes. For example, in an 80-node network, the RTDS reduces end-to-end latency by 58% and 43% in low and high traffic rates, respectively, compared to that in MSF. Further, it outperforms Stratum by 77% and 75% under the low and high traffic rates, respectively.

High‐intensity bird migration along Alpine valleys calls for protective measures against anthropogenically induced avian mortality

AbstractThe Alps are a natural barrier for avian broad‐front migration in Central Europe. While most birds that approach the Alps are deflected and circumvent the mountains, some choose to make the crossing. Here, they are funnelled and channelled in valleys, leading to high bird densities. Many Alpine valleys are suitable locations for wind farms, potentially creating a conflict between wind energy production and bird conservation. Collisions can be reduced by temporarily shutting down wind turbines. This however requires timely coordination, either by locally monitoring migration intensity or by extrapolating and forecasting migratory fluxes from other sites. However, little is known about the timing and intensity of bird migration in valleys of the central Alps, especially during spring migration. This study presents a 2‐year quantification of avian migration across the Alps. We collected terrestrial radar data at three sites: two located in Alpine valleys and one in the lowland, close to the northern foothills of the Alps. We found high migration traffic rates (MTR) during both migration seasons in the Alpine valleys, with outstanding numbers of migrants during the spring season. The strong alignment of the flight directions with the main orientation of alpine valleys highlights the importance of valleys and the connected passes in channelling migratory fluxes through the Alps. However, extrapolating migration intensities and forecasting peak migration events for inner Alpine sites is difficult, likely due to how migratory patterns and activity are influenced by the complexity of the local topography and the associated dynamic wind and weather conditions. Instead, we call for year‐round on‐site monitoring of migration intensities and strategies tailored to the local context to reduce the risk of bird strikes at wind turbines in the Alps.

Webcast marketing platform optimization via 6G R&D and the impact on brand content creation.

This work aims to investigate the development and management of cosmetics webcast marketing platforms, offering novel approaches for building and sustaining commercial brands. Firstly, an analysis of the current utilization of cosmetics webcast marketing platforms is conducted, identifying operational challenges associated with these platforms. Secondly, optimization strategies are proposed to address the identified issues by leveraging advancements in 6th Generation (6G) communication technology. Subsequently, a conceptual framework is established, employing big data interaction to examine the influence of webcast marketing platform experiences on brand fit. Multiple hypotheses are formulated to explore the relationship between platform experiences and brand fit. Finally, empirical analysis is performed within the context of the 5th Generation (5G) Mobile Communication Technology and extended to incorporate the 6G Mobile Communication Technology landscape. The results of the validation indicate the following: (1) the content generated by the webcast marketing platform has a positive impact on brand fit (β = 0.46, p<0.01; β = 0.31, p<0.05); (2) in the 6G network environment, a webcast marketing platform with high traffic transmission rates may enhance brand fit (β = 0.51, p<0.001); (3) the content generated by the webcast marketing platform exhibits significant positive regulatory effects on information-based and co-generated content (β = 0.42, p<0.01; β = 0.02, p<0.001). The findings of this work offer valuable insights for other scholars and researchers seeking to optimize webcast marketing platforms.

FIRST AID TRAINING IN ACCIDENT FOR SENIOR HIGH SCHOOL STUDENTS: EFFORTS TO IMPROVE STUDENT’S KNOWLEDGE AND SKILLS

Introduction: Lamongan is one of the areas on the north coast with very high traffic accident rate. First aid for accident victims is an important part of the management of accident victims. Students who are in the adolescent age group can become first responders for accident victims. The purpose of this community service activity is to increase students' knowledge and skills in providing first aid to accident victims. Methods: First aid training activities for accidents use lecture, discussion, demonstration and role play methods. The training participants were 50 students of SMKN 1 Lamongan. The material presented in the training includes basic life support, dressings and splints as well as evacuation and transportation. Training using audio visual media and teaching aids. Evaluation of the training using the questionnaires given at the beginning and at the end of the training. Results: The results of the pre test showed that 28 students (56%) had low knowledge, while 22 students (44%) had moderate knowledge. The results of the post test after being given education and training to students were as many as 20 students (40%) had moderate knowledge and 30 students (60%) had high knowledge. Conclusion: First aid training for accident victims for SMKN 1 Lamongan students can increase students' knowledge and skills in performing first aid to accident victims. Students are expected to act as first responders for traffic accident victims.

A Safe and Robust Autonomous Intersection Management System Using a Hierarchical Control Strategy and V2I Communication

Connected autonomous vehicles can significantly improve the safety and mobility of urban transportation systems. However, these systems are vulnerable to model uncertainties, wireless communication impairments, and external disturbances. In this article, we propose a new autonomous intersection management (AIM) system, called hierarchical model predictive control (HMPC). In HMPC, the intersection coordination unit (ICU) in a global centralized layer is responsible for assigning a safe speed to each vehicle while minimizing the system's cost. In the Local decentralized layer, each vehicle is responsible for tracking the reference speed assigned by the ICU, while avoiding collisions. In our method, each vehicle can use its own sensors to monitor its close surroundings, and take its own decisions on its movements, independent on the control decisions sent from the ICU. We investigate the safety, scalability and robustness of HMPC compared with two well-known AIM methods based on centralized and decentralized control strategies. For the evaluation, we use simulation of urban mobility (SUMO). Further, we study the scalability and performance of the algorithms in the presence of communication impairments associated with wireless channels. Our simulation results show that HMPC can safely handle high traffic flow rates. Also, HMPC is robust to uncertainties caused by the wireless communication.

Current and Future Trends in Driver Behaviour and Traffic Safety Scholarship: An African Research Agenda

Road traffic accidents are strongly associated with driver behaviour. Africa, as a region, has the highest road accident fatality rate, but there is very little research dealing with this critical issue on the continent. This paper, therefore, sought to establish the state of driver behaviour and road safety scholarship in Africa to determine current research trends as well as potential future research directions. To this end, two bibliometric analyses were conducted, one which considered the issue from an African perspective and the other which considered the broader body of work. The analysis revealed a critical shortage of research related to driver behaviour in Africa. The existing body of research primarily focused on the identification of issues and tended to focus on narrow research problems within limited geographical areas. A need was identified for the collection of broader macro-level data and statistical analyses thereof to indicate regional traffic crash patterns; causes and effects; country-level studies, particularly countries with high traffic fatality rates and low levels of research; cross-country comparisons; and modelling. Future research directions should also include the link between driver behaviour, traffic safety and the sustainable developments goals, as well as policy-related research to determine current and potential future country-level policies.

Effectiveness of an Entropy-Based Approach for Detecting Low- and High-Rate DDoS Attacks against the SDN Controller: Experimental Analysis

Software-defined networking (SDN) is a unique network architecture isolating the network control plane from the data plane, offering programmable elastic features that allow network operators to monitor their networks and efficiently manage them. However, the new technology is security deficient. A DDoS attack is one of the common attacks that threaten SDN controllers, leading to the degradation or even collapse of the entire SDN network. Entropy-based approaches and their variants are considered the most efficient approaches to detecting DDoS attacks on SDN controllers. Therefore, this work analyzes the feasibility and impacts of an entropy-based DDoS attack detection approach for detecting low-rate and high-rate DDoS attacks against the controller, measured in terms of detection rate (DR) and false-positive rate (FPR), triggered by a single or multiple host attacks targeting a single or multiple victims. Eight simulation scenarios, representing low and high DDoS attack traffic rates on the controller, have been used to evaluate an entropy-based DDoS attack detection approach. The experimental results reveal that the entropy-based approach enhances the average DR for detecting high-rate DDoS attack traffic compared with low-rate DDoS attack traffic by 6.25%, 20.26%, 6.74%, and 8.81%. In addition, it reduces the average FPRs for detecting a high DDoS attack traffic rate compared with a low DDoS attack traffic rate by 67.68%, 77.54%, 66.94%, and 64.81.

A virtual gateway media access placement approach for large-scale Internet of Things

The virtualisation of the Internet of Things (IoT) Gateway (GW) Media Access Control (MAC) component separates the GW MAC functions from the GW device by deploying the GW MAC functions in a selected remote edge Data Centre (eDC). This concept can help support media access for a large number of devices based on concurrent transmissions over Radio Frequency (RF) virtualisation. However, the requests for virtual GW MAC instances are dynamic and the virtual network is characterised by varying resource levels and response times. This can affect the throughput performance of the MAC protocol since the timing deadlines of the MAC functions or frame transmissions may not be met. In this work, the GW MAC functions of the IEEE 802.11ah standard for Large Scale IoT (LS-IoT) networks are virtualised as concurrent virtual Access Groups (vAGs) over a proposed Software Defined Network (SDN) virtual network. A virtual GW MAC placement strategy is proposed to optimally select the host for running the virtual GW MAC instances to minimise the virtualisation delay, improve the robustness of the deployment process and maintain a good MAC throughput performance. The results obtained in this work show that the virtualisation delay is minimised and the MAC throughput versus the number of devices is improved especially for high IoT traffic rates when compared to suboptimal approaches and the dedicated localised GW MAC approach.

An exploratory study of a law enforcement model for vehicle speed in Tshwane Metropolitan Municipality, South Africa

This study explores the law enforcement model for vehicle speed in Tshwane municipality of South Africa. South Africa has comparatively high road traffic crashes and casualty rates. Most of these crashes are associated with illegal speeding. This study was designed against the background of protracted road traffic crashes the triple causative factors as well as existing traffic law enforcement systems and processes aimed at managing illegal speeding. Data were collected from a sample of 28 senior law enforcement officials from the Tshwane Metropolitan Police Department (TMPD) traffic division, the Gauteng Traffic Police and the National Traffic Police. Qualitative data were analysed using thematic analysis’ open and axial coding processes on Atlas.ti.8. In its findings, the study developed a model that shows that illegal speeding and consequential road crashes were caused by an interaction of multiple factors. These were poor human behavioural elements as the main factor, road-environment factors and vehicle-related factors in the presence of inadequate and uncoordinated traffic law enforcement, weak penal systems for offenders, corruption, poor driver training and low road safety education.

Dynamic ways of using DAS with reduced call drops and hands-off

In today’s digital era people are controlled by digital gadgets, Cellular Systems are the backbone of these gadgets or cellular systems. Current technologies are offering more facilities to their users and also have a few challenges. In a cellular system, call dropping is one of the challenging problems, which is faced by a mobile user in a network due to many reasons like availability of free channels, low level of system configuration, high traffic rate, etc. In this research study, among various failures handover failure is one of the major reasons for call drops. A dropped call happens when your phone gets disconnected somehow from the cellular network. Usually, this happens because of poor cell signal wherever you are that causes the call to drop. When a handover failure exists, a call drop occurs. Many different techniques are proposed and introduced to remove the call drop problem. In this research proposed a proper load balancing for cellular signals using networking for efficient call drop-down solutions with the concept of the distributed antenna system.

Real-time network intrusion detection using deferred decision and hybrid classifier

The network intrusion detection system needs to detect intrusions in real-time without delay when an intrusion is attempted. To this end, various approaches, such as packet-based classifiers and session-based classifiers, have been developed, but there is a limitation in effectively reducing the detection delay. This study proposes a packet-based machine-learning model with a deferred decision and a single packet integration classifier with cumulative features based on this model to solve this problem fundamentally. A hybrid classifier that uses packet-based features and session-based features was combined to develop a new machine-learning-based network intrusion detection system. Unlike conventional methods, the proposed method could achieve very high detection accuracy and detect intrusions in real-time by minimizing the detection delay. In addition, it reached very high scalability, so it is easy to support high traffic rates and high concurrent session capacity. The performance was compared with various existing methods on various datasets. Through this, the superiority of the proposed method was proven. Overall, the current network can be protected more securely and quickly by applying the proposed method.

On Meeting a Maximum Delay Constraint Using Reinforcement Learning

Several emerging applications in wireless communications are required to achieve low latency, but also high traffic rates and reliabilities. From a latency point of view, most of the state-of-the-art techniques consider the average latency which may not directly apply to scenarios with stringent latency constraints. In this paper, we consider scheduling under a max-delay constraint; this is an NP-hard problem. We propose a novel approach to tackle the scheduling problem by directly addressing the constraint. We consider the downlink of a multi-cell wireless communication network with nodes communicating with users each facing their own delay constraint on randomly arrived packets. Packets must be scheduled to meet the users’ delay constraints. Our main contributions are first, proposing a new search approach, Super State Monte-Carlo Tree Search (SS-MCTS), as a version of regular MCTS modified for large-scale probabilistic environments; second, developing trained value and policy networks to reduce computational complexity, and finally, addressing the scheduling problem through a reinforcement learning framework. Our numerical results demonstrate that the proposed approach significantly improves the packet delivery rate over a baseline approach while meeting the max-delay constraint, and addressing the scalability as the main issues in large action-state spaces.

A Comparison of Approaches for the Time Series Forecasting of Motorway Traffic Flow Rate at Hourly and Daily Aggregation Levels

Congestion forms a large problem in many major metropolitan regions around the world, leading to delays and societal costs. Congestion is generally associated with reduced average speed at a high traffic flow rate. This traffic flow rate is defined as the number of vehicles that pass a certain location at a given time. The modelling and prediction of this traffic flow rate may lead to valuable insights that may be used to reduce congestion and societal costs. This study aims to predict the traffic flow rate for 41 different locations in and around Amsterdam, The Netherlands. Using TBATS, SARIMAX and LSTM models, among others, the traffic flow rate of these locations has successfully been modelled. These models may provide accurate predictions for the future flow rate, which may be useful for the identification of infrastructure bottlenecks and the scheduling of maintenance. Considering the dramatic effects of the COVID-19 pandemic on the traffic flow rate, the inclusion of 2020 data with a number of external factors, could lead to an improvement of the results and the ability to model the future effects of the pandemic.

Large-scale traffic flow simulation based on intelligent PSO

With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time.

Lane-change-aware connected automated vehicle trajectory optimization at a signalized intersection with multi-lane roads

Trajectory smoothing is an effective concept to control connected automated vehicles (CAVs) in mixed traffic to reduce traffic oscillations and improve overall traffic performance. However, smoother trajectories often lead to greater gaps between vehicles, which may incentivize human driven vehicles (HVs) from adjacent lanes to make cut-in lane changes. Such cut-in lane changes may compromise the expected performance from CAV trajectory smoothing. To figure out the reasons behind the issue, this paper designs a mixed traffic framework at a signalized intersection with multi-lane roads considering detailed trajectory control, car following and lane changing maneuvers all together. Based on the framework, this paper proposes a decentralized lane-change-aware CAV trajectory optimization model including discretionary lane change restraining and mandatory lane change yielding strategies. Riding comfort and traffic mobility are considered as a joint objective. And the complex non-linear lane-change-aware constraints are linearized to convert the proposed problem to a quadratic optimization problem. The linearization allows the investigated problem to be easily fed into a commercial solver. Numerical experiments are conducted to study the performance of the proposed model and to compare it with other models (e.g., a cooperative lane change model and a trajectory optimization model without the lane-change-aware mechanism) in different scenarios. First, results show that the HV lane changes cause reduction of half or more expected benefits of trajectory smoothing along a multi-lane segment adjacent to a signalized intersection. Then, we find that the proposed model outperforms the other models. Especially, the proposed model yields extra benefits in the system joint objective (10–25%), riding comfort (10–25%), travel time (1–8%), fuel consumption (3–15%) and safety (5–25%) compared with the trajectory optimization model without the lane-change-aware mechanism when CAV market penetration rate is not high. Sensitivity analyses on road segment lengths, signal cycle lengths, traffic saturation rates and through-vehicle rates show that the proposed model yields better system performance under most scenarios, e.g., 20% extra benefit at a short road segment length, 30% extra benefit at a long signal cycle length, 25% extra benefit at a high traffic saturation rate, and 25% extra benefit at a high through-vehicle rate.

Thorough Performance Evaluation &amp; Analysis of the 6TiSCH Minimal Scheduling Function (MSF)

IEEE Std 802.15.4-2015 Time Slotted Channel Hopping (TSCH) is the de facto Medium Access Control (MAC) mechanism for industrial applications. It renders communications more resilient to interference by spreading them over the time (time-slotted) and the frequency (channel-hopping) domains. The 6TiSCH architecture bases itself on this new MAC layer to enable high reliability communication in Wireless Sensor Networks (WSNs). In particular, it manages the construction of a distributed communication schedule that continuously adapts to changes in the network. In this paper, we first provide a thorough description of the 6TiSCH architecture, the 6TiSCH Operation Sublayer (6top), and the Minimal Scheduling Function (MSF). We then study its behavior and reactivity from low to high traffic rates by employing the Python-based 6TiSCH simulator. Our performance evaluation results demonstrate that the convergence pattern of MSF is the root cause of the majority of packet losses observed in the network. We also show that MSF is prone to over-provisioning of the network resources, especially in the case of varying traffic load. We propose a mathematical model to predict the convergence pattern of MSF. Finally we investigate the impact of varying parameters on the behavior of the scheduling function.